| | import gradio as gr |
| | import torch |
| | import numpy as np |
| | from PIL import Image |
| | from models import load_vision_model, get_image_transform, load_segmentation_model, DEVICE |
| | from diagnosis_module import diagnose_symptoms |
| | from pubmed_module import search_pubmed, summarize_text |
| |
|
| | |
| | vision_model = load_vision_model() |
| | seg_model = load_segmentation_model() |
| | transform = get_image_transform() |
| |
|
| | |
| | def analyze_image(image): |
| | if image is None: |
| | return "يرجى رفع صورة الأشعة" |
| | img = np.array(image.convert("RGB")) |
| | tensor = transform(img).unsqueeze(0).to(DEVICE) |
| | with torch.no_grad(): |
| | output = vision_model(tensor) |
| | probs = torch.softmax(output, dim=1).cpu().numpy()[0] |
| | top_classes = np.argsort(probs)[::-1][:5] |
| | result = "\n".join([f"فئة {i}: احتمال {probs[i]:.3f}" for i in top_classes]) |
| | return result |
| |
|
| | |
| | def analyze_symptoms_with_pubmed(symptom_text): |
| | if not symptom_text.strip(): |
| | return "يرجى كتابة الأعراض" |
| | |
| | results = diagnose_symptoms(symptom_text) |
| | |
| | text = "🔍 الأمراض المحتملة:\n\n" |
| | for r in results: |
| | text += f"- {r['disease']} (احتمال: {r['score']:.2f})\n📘 المصدر: {r['source']}\n" |
| | if r.get("brief"): |
| | text += f"📝 ملخص: {r['brief']}\n" |
| | |
| | |
| | articles = search_pubmed(r['disease']) |
| | if articles: |
| | text += "📰 أحدث الأبحاث:\n" |
| | for art in articles: |
| | summary = summarize_text(art['abstract']) if art['abstract'] else "لا يوجد ملخص" |
| | text += f"• {art['title']}\n ملخص: {summary}\n رابط: {art['link']}\n\n" |
| | |
| | return text |
| |
|
| | |
| | with gr.Blocks(title="MedAI Assistant") as app: |
| | gr.Markdown("# 🧠 MedAI — مساعد التحليل الطبي الذكي\n### ⚠️ لأغراض بحثية فقط، ليست بديلاً عن الطبيب") |
| |
|
| | with gr.Tab("تحليل الأشعة"): |
| | image_input = gr.Image(type="pil", label="📤 ارفع صورة الأشعة") |
| | image_output = gr.Textbox(label="🔍 نتائج التحليل") |
| | analyze_button = gr.Button("تشغيل التحليل") |
| | analyze_button.click(analyze_image, inputs=image_input, outputs=image_output) |
| |
|
| | with gr.Tab("تحليل الأعراض"): |
| | symptom_input = gr.Textbox(label="✏️ اكتب الأعراض (مثال: حمى، سعال، ضيق تنفس)") |
| | symptom_output = gr.Textbox(label="🩺 التشخيص + أبحاث PubMed") |
| | analyze_symptoms_btn = gr.Button("تشغيل التحليل") |
| | analyze_symptoms_btn.click(analyze_symptoms_with_pubmed, inputs=symptom_input, outputs=symptom_output) |
| |
|
| | app.launch() |
